Impairment detection with environmental considerations

ABSTRACT

A method and system for monitoring impairment indicators. The method comprises, during a first time window, measuring a first movement signal related to movement of a person with a movement sensor associated with the person, and measuring a first environmental signal with an environmental sensor. The method further comprises electronically storing at least one numerical descriptor derived from the first movement signal and the first environmental signal as reference data for the person. The method further includes, during a second time window, measuring a second movement signal related to movement of the person with the movement sensor and measuring a second environmental signal with the environmental sensor; and comparing at least one numerical descriptor derived from the second movement signal and the second environmental signal to the reference data to identify an impairment indicator.

TECHNICAL FIELD

The present invention relates to the field of recognizing or classifyingmovement, and more specifically, to identifying impairment indicatorsusing both data from a movement sensor and data from an environmentalsensor.

BACKGROUND

Detection of cognitive, physical, mental, sensory, emotional, ordevelopmental impairment is critically important in healthcare, lawenforcement, or other applications. Detection techniques may be specificto an individual impairment (such as physical) or any combination ofimpairments (such as cognitive and sensory). For example, detectingalcohol or controlled substance use or abuse by workers, individuals onparole, or in other contexts is important for safety and compliance withvarious restrictions. Detecting physical impairment, such as an injury,is important for workers who require full physical capabilities toperform their duties. Mental impairment detection is important inpotentially diagnosing patients with the early onset of minddebilitating conditions such as dementia and/or Alzheimer's disease.Detecting other impairments such as tiredness, distraction, andvestibular confusion play an important role for safety and compliancepurposes. Improved method for effectively monitoring for the presence ofimpairment without being invasive would be welcome.

SUMMARY

The present disclosure provides a new method of detecting impairmentindicators using data from both a movement sensor and an environmentalsensor. The present invention provides for non-intrusive continuousdetection of impairment indicators using multiple inputs. Upon detectionof an impairment indicator, a person may be required to perform furthertesting activities, thus reducing the overall need for and cost of typesof impairment testing such as drug or alcohol screening. Impairmentdetection is also useful to proactively identify and mitigate potentialsafety situations. Identification and notification when an individual isimpaired may reduce the amount of injuries or accidents that could occurotherwise. Additionally, using impairment detection for identifyingdiseases may lead to more effective treatment. Use of an environmentalsensor in combination with a movement sensor improves impairmentdetection by calibrating the device based on movement parameters withranges of environmental conditions, which eliminates false positives inimpairment detection.

In one aspect, the present invention includes a method for monitoringimpairment indicators. The method comprises, during a first time window,measuring a first movement signal related to movement of a person with amovement sensor associated with the person, and measuring a firstenvironmental signal with an environmental sensor. The method furthercomprises electronically storing at least one numerical descriptorderived from the first movement signal and the first environmentalsignal as reference data for the person. The method further includes,during a second time window, measuring a second movement signal relatedto movement of the person with the movement sensor and measuring asecond environmental signal with the environmental sensor; and comparingat least one numerical descriptor derived from the second movementsignal and the second environmental signal to the reference data toidentify an impairment indicator.

In some embodiments, the first time window occurs during a trainingactivity performed by the person.

In some embodiments, the method further comprises collecting locationinformation and using the location information as an additional factorto identify an impairment indicator.

In some embodiments, the impairment indicator is indicative of at leastone of mental impairment, visual impairment and physical impairment.

In some embodiments, the environmental sensor includes at least one of athermometer, a hygrometer, a sound meter, a particulate matter sampler,and an air quality meter.

In some embodiments, the environmental signal measures at least one oftemperature, air quality, humidity, sound level and particulate level.

In some embodiments, impairment includes at least one of physicalinjury, vestibular confusion, distraction and prohibited substanceabuse.

In some embodiments, the movement sensor is at least one of: anaccelerometer, a gyroscope, a piezoelectric vibration sensor, ageographical positioning sensor and a magnetic switch.

In some embodiments, the movement sensor is attached to the person.

In some embodiments, when an impairment indicator is detected, at leastone of a local alarm and a remote alarm is triggered.

In another aspect, the current disclosure includes a device formonitoring impairment indicators. The device comprises a housingconfigured to be attached to or carried by a person; an environmentalsensor; and a processing unit disposed in the housing comprising aprocessor and a movement sensor. During a first time window, themovement sensor measures a first movement signal related to movement ofthe person and the environmental sensor measures a first environmentalsignal. The processor stores at least one numerical descriptor derivedfrom the first movement signal and at least one numerical descriptorderived from the first environmental signal as reference data for theperson. During a second time window, the movement sensor measures asecond movement signal related to movement of the person and theenvironmental sensor measures a second environmental signal. Theprocessor compares at least one numerical descriptor derived from thesecond movement signal and at least one numerical descriptor derivedfrom the second environmental signal to the reference data to identifyan impairment indicator.

In some embodiments, the housing is one of: a safety garment, a harness,a head-worn piece, a device to be attached to a limb of the person or adevice used by the person.

In some embodiments, the device further includes a location module, andwherein the processor is configured to estimate a location of the personusing at least both of a signal from the movement sensor and data fromthe location module.

In some embodiments, the device further uses the location of the personas a second factor to identify an impairment indicator.

In some embodiments, the impairment indicator is indicative of at leastone of mental impairment, visual impairment and physical impairment.

In some embodiments, the movement sensor is at least one of: anaccelerometer, a gyroscope, a piezoelectric vibration sensor, ageographical positioning sensor and a magnetic switch.

In some embodiments, the device comprises more than one movement sensor.

In some embodiments, the movement of the person during the first timewindow is walking.

In some embodiments, when an impairment indicator is detected, at leastone of a local alarm and a remote alarm is triggered.

In some embodiments, the environmental sensor is at least one of: athermometer, a hygrometer, a sound meter, a particulate matter sampler,and an air quality meter.

In some embodiments, the environmental signal is at least one oftemperature, humidity, air quality, sounds level and particulate levels.

BRIEF DESCRIPTION OF DRAWINGS

The following figures provide illustrations of the present invention.They are intended to further describe and clarify the invention, but notto limit scope of the invention.

FIG. 1 is an example of a device for monitoring impairment indicatorsattached to a person.

FIGS. 2a and 2b are examples of housings for a device for monitoringimpairment indicators.

FIG. 3 is a flow chart representing a method of monitoring impairmentindicators.

FIG. 4 is a block diagram of a device for monitoring impairmentindicators.

Like numbers are generally used to refer to like components. Thedrawings are not to scale and are for illustrative purposes only.

DETAILED DESCRIPTION

FIG. 1 is an example of a device 10 for monitoring impairment indicatorsattached to a person's ankle 12. Device 10 is attached to person's ankle12 or other limb with strap 14. The housing 16 for device 10 includes orcontains a variety of components such as a processing unit 17, includinga processor, a movement sensor, and an environmental sensor and acommunication unit 18 for communicating wirelessly with an externaldevice. In some embodiments, the environmental sensor may be in aseparate device that is in communication with device 10. The processingunit may also include a location unit for determining a location of theuser of device 10. A processor in the processing unit 17 may alsoinclude memory for storing data received from the movement sensor,numerical descriptors, reference data, and other necessary informationto identify impairment indicators. The movement sensor may include atleast one of a variety of sensors, including an accelerometer,gyroscope, piezoelectric vibration sensor, geographical positioningsensor and a magnetic switch. The environmental sensor may include atleast one of a variety of sensors, including thermometer, a hygrometer,a sound meter, a particulate matter sampler, and an air quality meter.

A movement sensor may be configured to measure a signal related tomovement of the person during a first time window. The movement sensormay collect data at a variety of rates, for example, the rate may be inthe range of one (1) Hz to sixty (60) Hz. The rate may be, for example,5 Hz, 10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz or 60 Hz or more. The length ofthe time window may be any desired range. For example, a time window maybe in the range of two (2) seconds to ten (10) seconds. A time windowmay be, for example, 2 seconds, 5 seconds, 6 seconds, 10 seconds, ormore or less. The number of samples taken by a movement sensor in thedevice varies based on the length of the time window and the samplingrate. The number of samples may range, for example, from 8 to 1024samples. A processor may then electronically store at least onenumerical descriptor derived from the first movement signal as referencedata for the person. The numerical descriptor may be represented as ascalar such as a voltage, current, power, or energy measurement.

The environmental sensor can be configured to measure an environmentalsignal of the person during the first time window. The environmentalsignal may be, for example, temperature, air quality, humidity, soundlevel and particulate level. The environmental sensor may collect dataat a variety of rates, as appropriate for each sensor. For example, atemperature sensor may not need to take a read more than once per everyfew minutes; however, a sound meter may need to read data many times persecond. The frequency of sensor data collection is application specific.The environmental sensor may collect data at the same rate or atdifferent rates from the movement sensor. The environmental sensor maycollect the data during the same time window that the movement sensor iscollecting data, or during a time window that differs in time or lengthfrom the movement sensor data collection. A processor may thenelectronically store at least one numerical descriptor derived from thefirst environmental signal along with the numerical descriptor derivedfrom the first movement signal as reference data.

The movement sensor may then measure a second signal related to movementof the person during a second time window. The environmental sensor maythen measure a second signal related to person. The processor may thencompare at least one numerical descriptor derived from the secondmovement signal and at least one numerical descriptor derived from thesecond environmental signal to the reference data to identify animpairment indicator.

In one configuration, the first time window occurs during a trainingactivity performed by the person. In some embodiments training activitymay include, but is not limited to, a person completing a series ofprescribed or predetermined movements to establish baseline performancedata. In another configuration, the first time window is during normaluse of the device 10 by the person.

Device 10 may also include other components such as a location unit thatenables the device to receive satellite signals and determine locationusing, for example, GPS or the Global Navigation Satellite System(GLONASS) as discussed in U.S. Pat. No. 6,853,304 to Reisman et al.,incorporated herein by reference. A location unit may use other locationtechnologies such as triangulation using local WiFi signals or otherknown location technologies to estimate location of the activityrecognition device 10, and thereby the location of the person wearingthe device.

While device 10 is shown as having a housing of a device to be attachedto a limb of the person, the housing may be a variety of embodiments.For example, the housing may also be a safety garment, safety equipment,a harness, a head-worn piece, and article of clothing or incorporatedinto a handheld or portable device to be used by the person such as amobile phone.

While the housing for device 10 shows the movement sensor, environmentalsensor, processor and other device components being located in closeproximity to each other, in other housing configurations, theenvironmental sensor, the movement sensor, or multiple environmental ormovement sensors, may be located in multiple locations in the housing,and located at a distance from other components, including being locatedat a distance from the processor and communication unit. In thisconfiguration, the movement sensor and the environmental sensor arestill able to communicate with the other components through a wired orwireless communication connection. In some configurations, theenvironmental sensor may be located remotely from device 10 and may bein communication with device 10. In some configurations, a particularenvironment, such as a work site, may have multiple environmentalsensors, and device 10 may be in communication with more than onesensor, and may choose to communicate with the sensor in closestproximity to device 10.

FIGS. 2a and 2b are examples of housings for a device for monitoringimpairment indicators. FIG. 2a shows a high visibility safety vest 22.Vest 22 is a typical component of personal protective equipment (PPE)for many occupations and tasks, including construction, mining, roadwork, and in other fields and contexts. Vest 22 ensures that the wearercan be easily seen by, for example, other workers, oncoming vehicles anddrivers of equipment. Vest 22 may also be a housing for a device fordetecting impairment indicators. Movement sensors may be embedded atvarious locations in the vest, for example, at locations 24 a, 24 b, 24c, and 24 d. The variety of locations allows for increased reliabilityof movement data. Environmental sensors 21 a, 21 b and 21 c can also beembedded within the vest 22, or otherwise worn by the user. In someconfigurations, environmental sensors may be located in a place wherethey detect conditions of ambient air or other features of anenvironment that a user is working or present in without receivinginterference from a user associated with the environmental sensor. Vest22 may be designed to include a pocket or other holding mechanism tocarry other components of an impairment monitoring device. Pocket 23provides an exemplary accessible enclosure for components such as theprocessor, communication unit, battery and other components that may beenclosed in a single unit 25. Unit 25 may communicate with movementsensors at locations 22 a-22 d and environmental sensors at 21 a-21 cthrough a wired connection embedded or enclosed in vest 22, or through awireless connection.

FIG. 2b shows a hard hat 26 that also includes ear protection. Hard hat26 is an important piece of PPE that may be worn for many occupationsand tasks, including construction, mining, road work, along with otherfields and contexts. Hard hat 26 includes hearing protection muffs 27 aand 27 b. In some instances, muffs 27 a and 27 b may include noisecancellation capabilities and/or a speaker or othercommunication-related components. Hard hat 26 may be a housing for animpairment monitoring device. For example, movement sensors may belocated at various locations 28 a, 28 b, and 28 c throughout hardhat 26to allow for increased movement data reliability. Environmental sensorsmay be located at various locations throughout hardhat 26 such as atlocations 21 d, 21 e and 21 f.

Hard hat 26 may have a unit 29 including components such as a processor,communication unit, battery, and other components that may be enclosedin a single unit 29. Unit 29 may be in communication with movementsensors through a wired or wireless connection. In some instances, unit29 is integrated into the structure of hard hat 26 and in otherinstances (as illustrated in FIG. 2b ) it may be in a physicallyseparate structure from hard hat 26, and connected to the movementsensors embedded in hard hat 26 by a wired or wireless connection.

FIG. 3 is a flow chart representing a method of monitoring impairmentindicators. The method includes, in step 31 measuring, with a movementsensor attached to a person, a first signal related to movement of theperson during a first time window and measuring an environmental signalwith a environmental sensor associated with the person during the firsttime window. The first movement signal and the first environmentalsignal may include a variety of information. For example, the signalsmay be the output of a capacitive accelerometer measured as a scalarvoltage. The signals may also be the output of a piezoelectricaccelerometer measured as a scalar current or voltage. The time windowmay be any given period of time over which to measure the first signal.As described above, the time window may be in the range of two secondsto ten seconds, and may be between those numbers, shorter or longer. Insome instances, the movement sensor may measure the first signal overmultiple time windows to increase the sample size which increases theaccuracy of the measurement. In other instances, multiple sensors mayeach measure a signal related to movement of the person or multiplesensors may each measure a signal related to an environmental signalover the same time window. The plurality of data sets may increasereliability of measurement.

In some instances, the first time window occurs during a trainingactivity performed by the person. A training activity may be completedthrough a series of prescribed motions while the device is placed into aspecial training mode. The training could be performed by an authorizedtrainer (e.g., a parole officer or a safety manager), and the trainercould show the person wearing the device a video instructing them on thetypes of movements to perform during the training period. After thetraining period is complete, the trainer returns the device to a normalmonitoring mode.

In other instances, the movement of the person during the first timewindow occurs during their initial use of the impairment indicatordevice. In this case, the device begins detecting the movements of theperson to capture the signals associated with the user defined movement.The device also detects an environmental signal during that time periodto learn what typical movements in typical environments look like. Thedevice then may detect anomalies when newly measured signals arecompared to previously detected signals in similar environments. In someinstances, the movement of the person during the first time window iswalking, and in other instances, the movement may be another designatedmovement.

In step 32, the processor stores at least one numerical descriptorderived from each of the first movement signal and the firstenvironmental signal as reference data for the person. In someconfigurations, the processor may combine the first movement signal andthe first environmental signal to create a single numerical descriptorfor the combined signal. The numerical descriptor is a number computedbased on the data sampled from a signal measured by the movement sensoror by the environmental sensor. The numerical descriptor for each of themovement signal and the environmental signal may be based on a singlemeasured signal or on multiple measured signals. For example, when themovement sensor detects inertial movement along three axes, thenumerical descriptor may be calculated based on the data associated withone axis, any combination of two axes, a computation involving each ofthe three axes, or any combination thereof. The numerical descriptor maybe determined for each data point related to the measured signal(s) ormay be based on a lower sampling rate than the data from the measuredsignals. In some instances, two or more numerical descriptors may beassociated with each time window.

The numerical descriptor may be stored as reference data, forming abaseline for the particular type of movement for the individual. Forexample, when the activity performed by the person during the first timewindow is walking, the numerical descriptor for their activity during atleast the first time window is compared to future collected data toidentify indication of impairment of the person at that future time.

In step 33, the movement sensor measures a second signal related tomovement of the person during a second time window and the environmentalsensor measures a second signal related to an environmental signal. Thesecond time window may be chronologically adjacent to the first timewindow, or may be later in time. In some instances, the movement sensorand the environmental sensor may measure the second signal over multipletime windows to increase the sample size to provide a broader sample setfor comparison to reference data. In other instances, multiple sensorsmay each measure a signal related to movement of the person over thesame time window. The plurality of data sets may increase reliability ofmeasurement.

In step 34, the processor compares at least one numerical descriptorderived from the second movement signal and at least one numericaldescriptor derived from the second environmental signal to the referencedata as a factor to identify an impairment indicator. In anotherembodiment, the movement signal and the environmental signal may becombined such that a single numerical descriptor is derived from thecombined signal and then compared with the reference data. If there isalignment (within a tolerance) between the numerical descriptor and thereference data, the processor identifies normal behavior. Alignment maybe determined by a simple thresholding process and may also bedetermined by using a multi-dimensional classification algorithm, inwhich case multiple numerical descriptors would be required. In step 35,the processor determines if a match exists between the two signalswithin a tolerance. If there are sufficient differences between thereference data and second signal and a match does not occur as definedin the “no” path of step 35, then the processor identifies an impairmentindicator as shown in step 36. The parameters of detection of animpairment indicator can be tuned based on the application. Further, atolerance may be tighter where accurate identification of impairment iscritical or where there is a higher cost of impairment ismis-identified. An impairment indicator is indicative of at least one ofmental impairment, visual impairment and physical impairment. Thesetypes of impairments may include specific impairments. For example,mental impairment includes at least distraction. Visual impairmentincludes at least prohibited substance abuse. And physical impairmentincludes at least physical injury and vestibular confusion.

If a match exists between the two signals as identified in the “yes’path of step 35 or no impairment indicator is identified as defined instep 36, the device continues to measure movement by returning to step33. If an impairment indicator is detected, the device stores thatresult and in some instances, at least one of a local alarm and a remotealarm is triggered. The device then continues to measure movement asshown in step 33.

FIG. 4 is a block diagram of a device 40 for monitoring impairmentindicators. The device includes a processor 43, a movement sensor 44 andan environmental sensor 49. Processor 43 may be any type of processor ormicroprocessor commonly used to process information or to control avariety of other electronic components. Processor 43 interacts withmovement sensor 44 to receive data from movement sensor 44, such as asignal related to the movement of the person wearing impairmentmonitoring device 40. Movement sensor 44 may be configured to measuresuch a signal during a time window as defined by processor 43. Processor43 interacts with environmental sensor 49 to receive data fromenvironmental sensor 49. Such as a signal related to an environmentalsignal of the person wearing impairment monitoring device 40.Environmental sensor 49 may be configured to measure such a signalduring a time window as defined by processor 43.

Movement sensor 44 may be at least one of: an accelerometer, agyroscope, a piezoelectric vibration sensor, a geographical positioningsensor and a magnetic switch. Movement sensor 44 may include more thanone movement sensor. Movement sensor 44 measures a first signal relatedto movement of the person wearing impairment monitoring device 40 duringa first time window. The processor 43 stores at least one numericaldescriptor derived from the first signal as reference data for theperson. In some embodiments, the processor 43 may store the referencedata with an assigned activity label, such as walking, running, orbiking.

Environmental sensor 49 may be at least one of: electrocardiography,electroencephalography, electromyography, galvanic skin response, pulseoximeter, pressure transducer, photo resister, and thermistor sensors.Environmental sensor 49 may include more than one environmental sensor.Environmental sensor 49 measures a first signal related to anenvironmental signal of the person wearing impairment monitoring device40 during a first time window. The processor 43 stores at least onenumerical descriptor derived from the first environmental signal asreference data for the person.

An exemplary time window may be in the range of 2 (two) seconds to 10(ten) seconds and may contain a number of samples in the range of 8(eight) to 1024 samples, as an example, not as a limitation. Each ofenvironmental sensor 49 and movement sensor 44 may also be configured tooperate in a very low power mode where sampling takes place occasionallyover a longer time period, for example, once every five minutes, whenthe individual is sleeping or doing some other sedentary and longer-termactivity. In general, data collection by the movement sensor 44 orenvironmental sensor 49 could range between 0.2 Hz and 50 Hz infrequency, but is not limited to previously defined range. The datacollection frequency may be dependent upon the type of activity beingdetected. For example, faster moving activities, such as running, mayrequire a higher sample rate (closer to 50 Hz) than slower movingactivities such as sleeping. The size of a time window may also berelated to data collection rate. A time window should have enoughsamples for the data collected to store as reliable reference data.

Movement sensor 44 then measures a second signal related to movement ofthe person during a second time window and processor 43 compares atleast one numerical descriptor derived from the second movement signalto the reference data to identify an impairment indicator. Comparisonmay include an algebraic sum or difference or other statisticalvariation such as mean, standard deviation, or variance. In anembodiment, the first signal (or reference data) may be a voltagerepresented numerically as 3.3 volts and the second signal may berecorded (also numerically) as a voltage of 1.3 volts. Processor 43 maycompute the absolute difference between the first and second signal as2.0 volts and determine whether the variation is above or below athreshold that indicates impairment and triggers an alarm.

Environmental sensor 49 then measures a second signal related tomovement of the person during a second time window and processor 43compares at least one numerical descriptor derived from the secondenvironmental signal to the reference data to identify an impairmentindicator.

Movement sensor 44 and environmental sensor 49 may either be containedin the same physical unit as processor 43 or may be connected toprocessor 43 in a wired or wireless configuration.

Device 40 may further include a location unit 47. The location unit 47may be any device that provides an estimated geographical location forimpairment monitoring device 40. Examples of a location unit 47 includethe following technologies: GPS, Cellular Triangulation, WiFitriangulation and GNSS. In some configurations, processor 43 may beconfigured to estimate a location of the person using at least both ofthe signal from the movement sensor and data from the location unit. Insome configurations, device 40 may use the location of the person asestimated by location unit 47 as a second factor to identify animpairment indicator.

Device 40 may also include a communications unit 46 to allow device 40to communicate with external devices 48. For example, when an impairmentindicator is detected, a local alarm or a remote alarm in externaldevice 48 may be triggered.

While not shown in FIG. 4, impairment monitoring device 40 may furtherinclude an emergency notification component. Emergency notificationcomponent may be triggered manually, such as by a button or switch. Whenemergency notification component is triggered, communication unit 46 maytransmit information to external device 48. External device 48 may be acentral monitoring system, an emergency alert system, or other location.The information transmitted may include the location of device 40, thetime the emergency notification is transmitted, and the reason that theemergency notification is transmitted.

The signal from the movement sensor 44 is a digital representation (forexample, a number between 0 and 1023) of an analog voltage output fromthe sensor describing the motion

The techniques of this disclosure may be implemented in a wide varietyof computer devices, such as servers, laptop computers, desktopcomputers, notebook computers, tablet computers, hand-held computers,smart phones, and the like. Any components, modules or units have beendescribed to emphasize functional aspects and do not necessarily requirerealization by different hardware units. The techniques described hereinmay also be implemented in hardware, software, firmware, or anycombination thereof. Any features described as modules, units orcomponents may be implemented together in an integrated logic device orseparately as discrete but interoperable logic devices. In some cases,various features may be implemented as an integrated circuit device,such as an integrated circuit chip or chipset. Additionally, although anumber of distinct modules have been described throughout thisdescription, many of which perform unique functions, all the functionsof all of the modules may be combined into a single module, or evensplit into further additional modules. The modules described herein areonly exemplary and have been described as such for better ease ofunderstanding.

If implemented in software, the techniques may be realized at least inpart by a computer-readable medium comprising instructions that, whenexecuted in a processor, performs one or more of the methods describedabove. The computer-readable medium may comprise a tangiblecomputer-readable storage medium and may form part of a computer programproduct, which may include packaging materials. The computer-readablestorage medium may comprise random access memory (RAM) such assynchronous dynamic random access memory (SDRAM), read-only memory(ROM), non-volatile random access memory (NVRAM), electrically erasableprogrammable read-only memory (EEPROM), FLASH memory, magnetic oroptical data storage media, and the like. The computer-readable storagemedium may also comprise a non-volatile storage device, such as ahard-disk, magnetic tape, a compact disk (CD), digital versatile disk(DVD), Blu-ray disk, holographic data storage media, or othernon-volatile storage device.

The term “processor,” as used herein may refer to any of the foregoingstructure or any other structure suitable for implementation of thetechniques described herein. In addition, in some aspects, thefunctionality described herein may be provided within dedicated softwaremodules or hardware modules configured for performing the techniques ofthis disclosure. Even if implemented in software, the techniques may usehardware such as a processor to execute the software, and a memory tostore the software. In any such cases, the computers described hereinmay define a specific machine that is capable of executing the specificfunctions described herein. Also, the techniques could be fullyimplemented in one or more circuits or logic elements, which could alsobe considered a processor.

Variations on the disclosure described above will be apparent to one ofskill in the art upon reading the present disclosure, and are intendedto be included within the scope of the present disclosure. A wide rangeof activities may be detected in addition to those discussed explicitlyherein, and are within the scope of the present disclosure. Further, avariety of analysis methods may be used consistent with the disclosedanalysis steps and processes.

What is claimed is:
 1. A method for monitoring impairment indicators,the method comprising: during a first time window, measuring a firstmovement signal related to movement of a person with a movement sensorassociated with the person, and measuring a first environmental signalwith an environmental sensor; electronically storing at least onenumerical descriptor derived from the first movement signal and thefirst environmental signal as reference data for the person; during asecond time window, measuring a second movement signal related tomovement of the person with the movement sensor and measuring a secondenvironmental signal with the environmental sensor; comparing at leastone numerical descriptor derived from the second movement signal and thesecond environmental signal to the reference data to identify animpairment indicator.
 2. The method of claim 1, wherein the first timewindow occurs during a training activity performed by the person.
 3. Themethod of claim 1, further comprising collecting location informationand using the location information as an additional factor to identifyan impairment indicator.
 4. The method of claim 1, wherein theimpairment indicator is indicative of at least one of mental impairment,visual impairment and physical impairment.
 5. The method of claim 1,wherein the environmental sensor includes at least one of a thermometer,a hygrometer, a sound meter, a particulate matter sampler, and an airquality meter.
 6. The method of claim 1, wherein the environmentalsignal measures at least one of temperature, air quality, humidity,sound level and particulate level.
 7. The method of claim 4, whereinimpairment includes at least one of physical injury, vestibularconfusion, distraction and prohibited substance abuse.
 8. The method ofclaim 1, wherein the movement sensor is at least one of: anaccelerometer, a gyroscope, a piezoelectric vibration sensor, ageographical positioning sensor and a magnetic switch.
 9. The method ofclaim 1, wherein the movement sensor is attached to the person.
 10. Themethod of claim 1, wherein, when an impairment indicator is detected, atleast one of a local alarm and a remote alarm is triggered.
 11. A devicefor monitoring impairment indicators, the device comprising: a housingconfigured to be attached to or carried by a person; an environmentalsensor; a processing unit disposed in the housing comprising a processorand a movement sensor; wherein, during a first time window, the movementsensor measures a first movement signal related to movement of theperson and the environmental sensor measures a first environmentalsignal; wherein the processor stores at least one numerical descriptorderived from the first movement signal and at least one numericaldescriptor derived from the first environmental signal as reference datafor the person; wherein, during a second time window, the movementsensor measures a second movement signal related to movement of theperson and the environmental sensor measures a second environmentalsignal; and wherein the processor compares at least one numericaldescriptor derived from the second movement signal and at least onenumerical descriptor derived from the second environmental signal to thereference data to identify an impairment indicator.
 12. The device ofclaim 11, wherein the housing is one of: a safety garment, a harness, ahead-worn piece, a device to be attached to a limb of the person or adevice used by the person.
 13. The device of claim 11, wherein thedevice further includes a location module, and wherein the processor isconfigured to estimate a location of the person using at least both of asignal from the movement sensor and data from the location module. 14.The device of claim 13, further comprising using the location of theperson as a second factor to identify an impairment indicator.
 15. Thedevice of claim 11, wherein the impairment indicator is indicative of atleast one of mental impairment, visual impairment and physicalimpairment.
 16. The device of claim 11, wherein the movement sensor isat least one of: an accelerometer, a gyroscope, a piezoelectricvibration sensor, a geographical positioning sensor and a magneticswitch.
 17. The device of claim 11, wherein the device comprises morethan one movement sensor.
 18. The device of claim 11, wherein themovement of the person during the first time window is walking.
 19. Thedevice of claim 11, wherein, when an impairment indicator is detected,at least one of a local alarm and a remote alarm is triggered.
 20. Thedevice of claim 11, wherein the environmental sensor is at least one of:a thermometer, a hygrometer, a sound meter, a particulate mattersampler, and an air quality meter.
 21. The device of claim 11, whereinthe environmental signal is at least one of temperature, humidity, airquality, sounds level and particulate levels.